SPOT!: Map-Guided LLM Agent for Unsupervised Multi-CCTV Dynamic Object Tracking
Rattachement africain : kr. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
CCTV-based vehicle tracking systems face structural limitations in continuously connecting the trajectories of the same vehicle across multiple camera environments. In particular, blind spots occur due to the intervals between CCTVs and limited Fields of View (FOV), which leads to object ID switching and trajectory loss, thereby reducing the reliability of real-time path prediction. This paper proposes SPOT (Spatial Prediction Over Trajectories), a map-guided LLM agent capable of tracking vehicles even in blind spots of multi-CCTV environments without prior training. The proposed method represents road structures (Waypoints) and CCTV placement information as documents based on 2D spatial coordinates and organizes them through chunking techniques to enable real-time querying and inference. Furthermore, it transforms the vehicle's position into the actual world coordinate system using the relative position and FOV information of objects observed in CCTV images. By combining map spatial information with the vehicle's moving direction, speed, and driving patterns, a beam search is performed at the intersection level to derive candidate CCTV locations where the vehicle is most likely to enter after the blind spot. Experimental results based on the CARLA simulator in a virtual city environment confirmed that the proposed method accurately predicts the next appearing CCTV even in blind spot sections, maintaining continuous vehicle trajectories more effectively than existing techniques.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
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Où se fait cette recherche
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Kwangwoon University pays non établi dans la noticeUniversité ou école supérieure
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Gwangju Institute of Science and Technology pays non établi dans la noticeUniversité ou école supérieure
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Gwangju University pays non établi dans la noticeUniversité ou école supérieure
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Artificial Intelligence Engineering College of Software and Convergence pays non établi dans la noticeUniversité ou école supérieure
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Mechanical Engineering Gwangju Institute pays non établi dans la noticeStructure de recherche
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of Science And Technology (GIST) GwangJu pays non établi dans la noticeInstitution
Kwangwoon University, Gwangju Institute of Science and Technology et Gwangju University, avec 3 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.